metadata
base_model: dmis-lab/selfbiorag_7b
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: selfbiorag-7b-dpo-full-wo-kqa_silver_wogold-ep3
results: []
selfbiorag-7b-dpo-full-wo-kqa_silver_wogold-ep3
This model is a fine-tuned version of dmis-lab/selfbiorag_7b on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6392
- Rewards/chosen: 0.1232
- Rewards/rejected: -0.0030
- Rewards/accuracies: 0.7527
- Rewards/margins: 0.1262
- Logps/rejected: -171.6258
- Logps/chosen: -150.9050
- Logits/rejected: -1.5645
- Logits/chosen: -1.7964
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6608 | 0.25 | 100 | 0.6631 | 0.1074 | 0.0395 | 0.7107 | 0.0680 | -167.3843 | -152.4830 | -1.5362 | -1.7612 |
| 0.6271 | 0.51 | 200 | 0.6474 | 0.1331 | 0.0272 | 0.7455 | 0.1060 | -168.6118 | -149.9109 | -1.5243 | -1.7495 |
| 0.61 | 0.76 | 300 | 0.6403 | 0.1251 | 0.0020 | 0.7554 | 0.1232 | -171.1355 | -150.7145 | -1.5597 | -1.7911 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2